The research team, led by Veronica Kamanzi of the University of Jyväskylä in Finland together with Tuomo Virtanen, Marja-Kristiina Lerkkanen, and Sirpa Eskelä-Haapanen, interviewed 30 pre-primary teachers across 16 government primary schools in three Tanzanian regions: Dar-es-Salaam, Dodoma, and Manyara. Fifteen schools were chosen by simple random sampling to capture the general state of inclusive literacy instruction in urban and peri-urban areas, while one Dar-es-Salaam school was purposively selected because it is a government-designated site where children with and without disabilities learn together. That hybrid design served a clever diagnostic purpose: if even the best-resourced ‘best-case’ school showed the same pedagogical tensions as randomly selected sites, the problems could be attributed to systemic causes rather than poor school-level management. That is precisely what the analysis found, although the authors acknowledge the possibility of a best-case bias in their sampling.

Semi-structured interviews lasting 48 to 60 minutes were conducted in Swahili, transcribed, translated into English with cross-checking by a bilingual language expert, and analyzed using reflexive thematic analysis that combined inductive coding with deductive interpretation against the theoretical framework of inclusive pedagogy. Four key themes emerged from teachers’ accounts: their teaching experience, their understanding of inclusive pedagogy itself, the strategies they use to identify children with diverse needs, and the ways they adapt literacy lessons. Five major challenge categories followed: curriculum constraints, environmental limitations, resource scarcity, professional development gaps, and inadequate institutional support for children with special literacy needs.

The conceptual heart of the study lies in distinguishing inclusive pedagogy from mere accommodation. Drawing on the influential framework of Florian and Black-Hawkins, the authors define inclusive pedagogy not as a set of techniques but as a pedagogical stance resting on three assumptions: differences among learners are an ordinary aspect of human development; teachers are responsible for teaching all learners, not only those who fit normative expectations; and teaching should extend opportunities for all rather than provide separate alternatives for some. This contrasts sharply with accommodation-based models, in which additional provision is made only after learners are identified as having diverse needs. The distinction matters technically because it changes when and how adaptation happens—embedded in initial lesson design versus bolted on afterward.

Measured against that standard, the Tanzanian teachers’ understanding of inclusive pedagogy was highly variable and often incomplete. Nearly all participants equated pedagogy with practical classroom strategies, methods, and approaches. Some could not define the concept at all; one teacher described it as ‘raising the children together,’ while another called it simply ‘a mixed approach using various teaching strategies.’ Even teachers who framed inclusion as engaging all children, including those with and without disabilities, tended to think in categorical terms about identified learners rather than designing lessons that never separate or marginalize anyone in the first place. The researchers interpret this pattern as a direct consequence of limited preparation: teachers who lack training default to viewing inclusion as a collection of techniques rather than a principled framework.

Teachers did show genuine, often inventive, effort in recognizing learner diversity. They described five identification strategies: gathering information from parents during registration, using questioning techniques to reveal speech or emotional difficulties, observing children’s peer interactions and participation, monitoring how children complete learning tasks, and interacting with children during informal moments such as playtime and morning circles. One teacher explained that when a child stays silent after a question, ‘it indicates that they may have a certain challenge that needs special attention.’ Yet the authors note that these strategies are largely non-standardized and dependent on individual judgment, and their strong focus on identifying ‘children with diverse learning needs’ leans toward categorization rather than the proactive, non-categorical design that inclusive pedagogy demands.

When it came to adapting literacy lessons, teachers relied on teaching aids prepared by hand, flexibility in delivery, and varied strategies such as songs, teaching from simple to complex, repetition, and hands-on activities. One teacher described showing a picture of the letter ‘b,’ demonstrating how to write it, and then offering multiple letters for children with diverse needs to identify. Another explained that she teaches everyone together first and only afterward takes extra time to assist children with challenges individually. That sequencing is technically revealing: inclusion was consistently described as something added after whole-class instruction rather than embedded in the lesson plan itself—a hallmark of the accommodation model the study set out to diagnose.

The structural barriers the teachers described are formidable. Although Tanzania’s curriculum prescribes a pre-primary teacher-to-child ratio of 1:25, actual ratios ranged from 1:70 to 1:80, with some peri-urban and urban classes exceeding 100 children per teacher. Furniture was often built for older children, leaving no space for play or interaction. Teachers improvised materials with their own money and time, but acknowledged that improvised aids cannot substitute for large-print books, braille, hearing aids, lenses, or ICT tools such as tablets and screens. Professional development was scarce and shallow—one teacher recalled a single three-day seminar devoted only to the new curriculum—and teachers reported contradictory interpretations of whether the curriculum permits or requires children to begin writing letters immediately, a confusion the authors link to unclear guidance and uneven literacy experiences across classrooms.

The study’s conclusion is sobering but constructive: positive attitudes and personal motivation cannot compensate for missing pedagogical skills, absent resources, and weak institutional leadership. Tanzania has strong policy frameworks, including the Education Sector Development Plan and the National Strategy for Inclusive Education, but these provide limited operational guidance for everyday classroom practice, and teachers report receiving little administrative support for their inclusion efforts. The authors call for targeted in-service training in inclusive pedagogy, curriculum adjustments with clearer guidance, improved access to specialized teaching and learning resources, and stronger institutional leadership, including a dedicated administrative focus on early childhood education. They also caution that their findings rest on self-reported perceptions without classroom observation, so future research should triangulate interviews with observed practice. The broader message resonates far beyond Tanzania: meaningful inclusion in early literacy depends not only on teachers’ commitment, but on the systems that enable them to act on it.

Subject of Research: Pre-primary teachers' perceptions and implementation of inclusive pedagogy for early literacy acquisition in Tanzania

Article Title: Pre-primary teachers’ perceptions of the implementation of inclusive pedagogy for literacy acquisition in Tanzania

Article References: Kamanzi, V., Virtanen, T., Lerkkanen, M.-K., & Eskelä-Haapanen, S. (2026). Pre-primary teachers’ perceptions of the implementation of inclusive pedagogy for literacy acquisition in Tanzania. Discover Education, 5(1), Article 1146. https://doi.org/10.1007/s44217-026-02262-7

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02262-7

Keywords: inclusive pedagogy, literacy acquisition, pre-primary education, Tanzania, teacher perceptions, early childhood education, teacher training, inclusive education policy, qualitative research, thematic analysis, learner diversity, educational resources

The rationale for the work rests on a well-documented paradox. Both individual educators and the institutions that govern them recognize the benefits of applying educational evidence to teaching, yet the gap between academic research and frontline practice has persisted since at least the early 1990s, when Charles Kaestle famously described the awful reputation of education research. Previous studies have traced the problem to multiple, overlapping causes. Research competence is poorly integrated into initial teacher education, so many graduates never learn to interpret studies or judge the quality of evidence. Few professionals are trained to distinguish reliable findings from unfounded claims. Time is another critical constraint: teachers are unwilling to invest scarce hours in engaging with research, and those in leadership positions are often unwilling to fund the resources that would make such engagement feasible.

The new study also highlights subtler obstacles that operate at the psychological and structural level. Teachers may resist change because new evidence conflicts with pre-existing beliefs and values, a phenomenon long noted in the literature. Research on teacher effectiveness suggests a kind of ossification: classroom effectiveness improves rapidly during the first five to seven years of teaching and then plateaus, a shift the authors of that earlier work attribute to the transition from deliberate, reflective practice to habitual routines at the neural level. Meanwhile, the way scientific articles are written poses an accessibility problem in itself, and the realities of a given classroom often differ so much from the conditions of the original research that teachers judge the findings irrelevant. Political pressures and the rush to publish significant results can further compromise research quality and ethics, leading society to confuse impact with quality and to adopt ineffective practices.

Against this backdrop, the researchers set out to build a measurement tool rather than another exhortation to collaborate. Their questionnaire follows a cross-sectional design and draws on Dillman’s Tailored Design Method, a framework for constructing surveys that produce valid and reliable results. Questions were drafted with clarity, impartiality, and conciseness in mind, each addressing a single element. Crucially, the instrument defines what it means by educational research and scientific evidence, ensuring that all respondents share a common conceptual framework, since definitions of research can vary widely across the teaching population. The questionnaire measures three main variables on five-point Likert scales: perception of barriers to accessing and transferring scientific evidence, perception of potential facilitators, and perception of the potential of new technologies to help teachers integrate evidence into the classroom.

Content validity was established through a formal expert judgment process. Eleven experts, nine from the university sector and two schoolteachers with university affiliations, evaluated every item for comprehension, relevance, and importance. Selection criteria required experience in education and educational technologies, training in scientific research, more than three years of professional experience, and membership of different educational bodies and institutions. The experts’ own competence was quantified using the K Coefficient, or Expert Competence Coefficient, which combines a knowledge coefficient with an argumentation coefficient. The results were reassuring: most experts scored above 0.8, indicating high competence, with only two in the medium range. Every item received an average score above 3.5 out of 4, and with the standard threshold of 80 percent expert agreement met, all items were retained for the pilot phase.

The pilot test involved 278 students enrolled in the Master’s Degree in Teacher Training at four Catalan universities: Universitat de Lleida, Universitat Ramon Llull, Universitat Rovira i Virgili, and Universitat de Vic. Drawn from a total population of 450 prospective secondary teachers through non-probabilistic convenience sampling, the sample exceeded the 259 participants calculated as necessary for a 99 percent confidence level with a 5 percent margin of error. The questionnaire was distributed by email and in person, with students able to respond via a QR code on their mobile devices. Notably, 37.05 percent of the sample combined their studies with active teaching work, a situation the authors describe as distinctive to the Catalan context.

The statistical analysis is where the study earns its technical credibility. Because Mardia’s multivariate kurtosis coefficient of 18.963 indicated non-normal data, the researchers selected the Weighted Least Squares estimation method, chosen for its robustness against departures from normality in exploratory factor analysis. Sampling adequacy was confirmed with a Kaiser-Meyer-Olkin value of 0.847, comfortably above the 0.80 threshold considered good, and Bartlett’s test of sphericity was highly significant. An oblique Promax rotation was applied to allow factors to correlate, and the resulting correlation matrix justified that choice. Applying the Kaiser criterion, a scree test, and a parallel analysis comparing observed eigenvalues against those from random data, the team retained seven factors, each represented by at least three items with loadings above the 0.32 significance threshold.

The seven factors tell a coherent story about what shapes evidence use. Factor 1 captures technology as a facilitator, addressing how digital tools can help integrate scientific evidence into classrooms. Factor 2 reflects institutional support, including time to implement evidence and the accessibility of research in terms of language and complexity; a negatively loading item within this factor signals that research lacking relevant conclusions for practice can undermine even improved access. Factor 3 concerns direct contact between teachers and research teams. Factor 4 covers educational resources, Factor 5 groups relevance, accessibility, and practicality, Factor 6 encompasses physical and cognitive barriers to accessing scientific articles, and Factor 7 measures the value of scientific literature itself as a professional resource. Reliability analysis showed Cronbach’s Alpha values above 0.7 for all factors except Factor 7, which scored 0.492; the authors retained it because its eigenvalue exceeded 1 and its low consistency likely reflects the small number of items, while also noting that merging it with Factor 4 would have produced an acceptable alpha of 0.764.

The practical implications extend well beyond psychometrics. By mapping the latent structure of teachers’ perceptions, the instrument gives policymakers, teacher educators, and researchers a diagnostic tool for identifying exactly where the pipeline from evidence to practice breaks down, whether at the point of access, interpretation, institutional backing, or technological support. The authors acknowledge limitations: convenience sampling limits representativeness, and the sample of Catalan master’s students may not generalize to the broader teaching population. They propose administering the questionnaire to more active teachers across experience levels and complementing future quantitative analyses with qualitative and mixed-methods designs to strengthen validity. Still, the study delivers what Kaestle argued was essential decades ago: a clear picture of the frontline of the system. With a validated instrument now available, the dialogue between educational research and classroom practice has, for the first time, a reliable way to measure itself, and a concrete pathway toward closing a gap that has persisted for more than thirty years.

Subject of Research: Design and validation of a self-perception questionnaire on teachers' use of scientific knowledge in teaching practice

Article Title: Design and validation of a self-perception instrument on the use of scientific knowledge in teaching practice

Article References: Guinovart-Pedescoll, M., & Palau, R. (2025). Design and validation of a self-perception instrument on the use of scientific knowledge in teaching practice. Journal of New Approaches in Educational Research, 14(1), Article 3. https://doi.org/10.1007/s44322-024-00026-5

Image Credits: AI Generated

DOI: 10.1007/s44322-024-00026-5

Keywords: educational research, scientific evidence, questionnaire validation, teacher training, exploratory factor analysis, evidence-based practice, teaching quality, research-practice gap, psychometrics, educational technology, Catalonia, teacher perceptions

The research, conducted by a team at Universitas Negeri Semarang and published in Discover Education, recruited participants through e-Guru.id, an Indonesian online professional learning network that offers webinars, memberships, and specialized training. All respondents had completed at least one MOOC related to professional development. The sample was predominantly female, with 1,665 women and 866 men, and professionally seasoned: nearly 78 percent were aged 35 or older, and almost 57 percent had at least 15 years of classroom experience. Notably, despite that deep experience, most were newcomers to MOOC learning, with 82.3 percent reporting zero to two years of MOOC use. The authors caution that because recruitment relied on a digitally connected professional network, the sample should not be treated as nationally representative of all Indonesian teachers.

Methodologically, the study is a cross-sectional survey designed to describe and explore rather than to test causal claims. Each of three conceptual domains was measured with five items on a four-point Likert scale, a format chosen to push participants toward a directional response rather than a neutral midpoint. The three domains were Perceived MOOC Effectiveness, covering instructional value, relevance, and professional usefulness; Perceived Professional Competence and Confidence, covering motivation and the perceived ability to apply new knowledge; and Perceived Opportunities and Challenges, covering scheduling flexibility, collaboration, effort, institutional support, and workload. Before any group comparisons, the team validated the instrument with confirmatory factor analysis using IBM SPSS Amos, and the three-factor model showed excellent fit, with a Comparative Fit Index of 0.972, a Tucker-Lewis Index of 0.967, and a Root Mean Square Error of Approximation of 0.057.

The statistical machinery behind the subgroup comparisons deserves attention because it reflects a growing standard of rigor in educational research. Rather than relying on classical analysis of variance, the team used Welch’s independent-samples t-tests and Welch’s one-way ANOVAs, which do not assume equal variances and are better suited to the substantially unequal group sizes in the sample. Because 15 item-level comparisons were run for each demographic variable, the researchers applied Benjamini-Hochberg false discovery rate corrections within each family of tests, and they followed significant omnibus results with Games-Howell post hoc tests. Effect sizes were reported as Cohen’s d for gender comparisons and as eta squared and omega squared for the ANOVAs. Of 75 item-level comparisons across five grouping variables, only three survived correction, a result the authors interpret as evidence of greater similarity than difference across teacher groups.

The descriptive findings tell a coherent story about what teachers value. Within the effectiveness domain, item means ranged from 3.42 to 3.64 on the four-point scale, with the highest rating going to the statement that MOOCs provide valuable resources and materials for improving teaching practice. Close behind were items on the contribution of MOOCs to understanding pedagogical strategies and instructional design, the relevance of content to classroom teaching, and usefulness for professional growth. The lowest item in the domain, though still positive, concerned perceived benefits for student learning, suggesting that teachers were more confident identifying immediate professional gains for themselves than attributing changes in student outcomes to their course participation. The authors stress that student outcomes were not measured independently, so this item reflects perception rather than demonstrated achievement gains.

The competence and confidence results reveal a subtle but important gap. Teachers rated their motivation to teach and share knowledge after MOOC participation highest, at a mean of 3.56, followed closely by perceived improvement in teaching skills. But confidence in applying MOOC-acquired knowledge in practice and in integrating technology into classroom teaching scored slightly lower, at 3.46 and 3.45 respectively. The authors argue this distinction separates professional learning acquisition from professional learning transfer: teachers may absorb knowledge and feel motivated, yet still struggle to translate that knowledge into technology-supported classroom practice. Because the data are self-reported and cross-sectional, the findings capture perceptions of capability rather than independently verified changes in instructional performance.

The opportunities-and-challenges domain produced the most differentiated pattern and the study’s most striking single result. Teachers rated opportunities to collaborate with colleagues across Indonesia highly, at a mean of 3.50, and valued the flexibility of MOOCs amid busy schedules at 3.45. Yet the item measuring difficulty completing MOOCs because of workload or other commitments scored an identical 3.45, and the effort required to keep up with course content scored 3.39. Flexibility, in other words, did not eliminate the demands of participation; it reorganized them. The lowest mean across the entire survey went to institutional support, at just 3.03, with a large standard deviation of 0.92 indicating wide variation in teachers’ experiences of organizational backing. The authors suggest that many participants may not have experienced MOOC learning as embedded within school-level professional development structures.

The subgroup analysis dismantles several common assumptions about who benefits from online professional learning. After false discovery rate correction, age, educational attainment, and teaching experience showed no robust differences on any of the 15 items, challenging narratives that frame digital learning through generational or qualification-based divides. Only two small gender differences survived correction: male teachers reported slightly higher perceived scheduling flexibility and slightly stronger institutional support, with Cohen’s d values of just -0.12 and -0.13. A nominal gender gap in technology-integration confidence vanished after adjustment. The one substantive pattern involved duration of MOOC use: teachers with more than six years of experience rated content relevance significantly higher than newer users, though the omnibus effect was small, explaining less than 1 percent of variance, and the longest-duration group contained only 74 participants. The authors note that causality cannot be inferred; sustained participants may find courses more relevant, or prolonged engagement may sharpen their ability to identify relevant content.

What emerges is a socio-technical picture in which MOOCs are not standalone solutions but components of broader professional learning ecosystems. The authors argue that access to online courses does not automatically become meaningful professional growth, and that knowledge acquired through MOOCs requires opportunities for experimentation, reflection, feedback, and institutional support before it becomes classroom practice. The coexistence of high flexibility ratings with high workload ratings exposes what they call a common misconception: that accessibility translates into ease of participation. For working teachers, flexible delivery shifts rather than removes the burden of allocating time, sustaining motivation, and balancing coursework against teaching and administrative duties. Barriers, they conclude, are organizational and temporal as much as technological.

The practical implications point away from demographic targeting and toward the conditions surrounding participation. The authors recommend designing relevant, practice-oriented content, reducing unnecessary workload, fostering collaborative learning communities, and embedding MOOCs within school-based professional development structures that provide recognition, mentoring, and protected time. They are careful to frame these as priorities for program development whose effects require direct evaluation, not proven interventions. The study’s limitations, including its cross-sectional design, self-reported data, and convenience sampling, restrict causal interpretation and generalizability. Future research, the team suggests, should employ longitudinal, mixed-method, and performance-based designs to examine whether MOOC participation actually changes instructional practice, how perceptions evolve over time, and which institutional conditions sustain engagement. For now, the message for education systems betting on MOOCs at scale is clear: teachers are ready and willing, but the surrounding ecosystem must catch up.

Subject of Research: Indonesian teachers' perceptions of massive open online courses for continuing professional development

Article Title: Indonesian teachers’ perceptions of MOOCs for digital professional development

Article References: Iqdami, M. N., Haryono, Astuti, T., & Widhanarto, G. P. (2026). Indonesian teachers’ perceptions of MOOCs for digital professional development. Discover Education, 5(1), Article 1080. https://doi.org/10.1007/s44217-026-02170-w

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02170-w

Keywords: MOOCs, teacher professional development, Indonesia, online learning, continuing professional development, survey research, institutional support, workload, teacher perceptions, digital learning, Discover Education, statistical analysis

The authors cast a deliberately wide net. They searched four major databases: Web of Science, Scopus, the TR Index, and the Higher Education Council National Thesis Center, which catalogs graduate theses from Turkish universities. That last source matters enormously, because in Türkiye a large share of curriculum research has been produced by master’s and doctoral students rather than by established academics publishing in indexed journals. The team then applied thematic content analysis, a technique that codes each study according to categories such as research method, participant group, data collection instrument, and topic, allowing patterns across hundreds of individual investigations to emerge from the aggregate.

The clearest signal in the data is temporal. Interest in mathematics curriculum research did not accumulate steadily; it surged after major policy interventions. Türkiye revised its mathematics curriculum repeatedly during the review period, with official documents issued in 2005, 2009, 2013, 2018, and most recently 2024 under the so-called Türkiye Century Maarif Model. Each revision triggered a fresh burst of studies examining what had changed, how teachers interpreted the new documents, and whether the intended innovations were reaching classrooms. The review’s authors describe this reform-driven rhythm as the dominant force shaping the field’s trajectory, with publication peaks tracking closely behind official curriculum updates.

Methodologically, the picture is lopsided. Most of the studies reviewed employed qualitative designs, with case studies and document analyses dominating the landscape. Document analyses, in particular, became a signature approach: researchers compared successive curriculum documents against one another, evaluated them through established frameworks such as Tyler’s objectives-based model, Stufflebeam’s CIPP model, or Eisner’s educational criticism model, and examined how constructs like mathematical literacy, estimation skills, geometric habits of mind, and twenty-first-century skills were represented across different eras. Quantitative and mixed-methods work, by contrast, occupied a much smaller share of the literature, and experimental designs were rare.

The instruments researchers used tell a similar story. Surveys, interviews, observations, and achievement tests were the workhorses of data collection, reflecting the field’s preoccupation with capturing perceptions rather than measuring outcomes. That preoccupation extends to who was studied. The overwhelming majority of investigations focused on mathematics teachers and classroom teachers, soliciting their views on the curriculum, their concerns during implementation, and their proficiency with the assessment methods the reforms demanded. Studies probing how students experienced the curriculum, or how it affected learning over time, were comparatively scarce.

Thematically, three clusters stand out. The first concerns teachers’ perceptions of the curriculum: how they understood the constructivist philosophy underlying the 2005 reform, what worries they expressed during its first year, and how they judged its feasibility in real classrooms. The second is curriculum evaluation, a genre in which researchers systematically appraised official documents against theoretical criteria. The third is comparison, both national and international. Turkish scholars have compared their curricula with those of Estonia, Canada, and Singapore, and have traced the historical evolution of their own programs back through the republican period and even to 1948, examining how general aims, content organization, and pedagogical principles shifted across generations of reform.

That historical thread is one of the field’s genuine strengths. Studies have analyzed curricula dating from 1924 onward, charting the rise of the spiral approach, in which topics are revisited at increasing levels of sophistication, and documenting the long arc from behaviorist aims toward competency-based goals. Such work situates Türkiye’s recent reforms within a century-long story of educational modernization and connects national debates to international frameworks like the National Council of Teachers of Mathematics standards, which influenced the 2005 redesign. For international readers, the review offers a case study in how a single national system has repeatedly translated global curriculum theory into local policy.

Yet the review’s most consequential finding is what is missing. Despite the volume of research, the authors conclude that the field has expanded in breadth while remaining limited in depth, particularly regarding comprehensive evaluation of how curricula are actually implemented and whether they work. School administrators and parents, the stakeholders who shape and experience curriculum reform from outside the classroom, are almost entirely absent from the literature. And because so few studies used experimental, longitudinal, or action research designs, the field can say a great deal about what documents intend and what teachers think, but very little about causal effects on student learning or about how implementation unfolds over multiple years.

The authors’ prescription follows directly from the diagnosis. They call for experimental and longitudinal studies capable of testing whether curricular changes improve outcomes, for action research that embeds evaluation within teachers’ own practice, and for mixed-methods approaches that combine the interpretive richness of qualitative work with the inferential power of quantitative measurement. They also argue that the accumulated evidence now needs synthesis at a higher level: meta-analyses that pool effect estimates across studies, and bibliometric analyses that map the intellectual structure of the field, would convert two decades of scattered findings into a coherent knowledge base capable of informing the next round of reform.

The stakes extend well beyond Türkiye. Curriculum reform is a global industry, and the Turkish experience mirrors patterns documented elsewhere: reforms announced with ambitious constructivist rhetoric, followed by studies of teacher buy-in, followed by persistent uncertainty about impact. The review suggests a cautionary lesson for education systems everywhere. A research literature can be voluminous and still leave the central question, does this curriculum help students learn mathematics, unanswered. Closing that gap requires not more perception studies but a deliberate shift toward designs that can track implementation and measure effectiveness over time. As Türkiye prepares to implement its 2024 Maarif Model curriculum, the review offers both a map of what has been learned and a warning about what remains unknown.

Subject of Research: Systematic review of mathematics curriculum research trends in Türkiye over two decades

Article Title: A systematic review of mathematics curriculum studies in Türkiye: trends and insights over two decades

Article References: Birgin, O., & Türkmen, H. İ. (2026). A systematic review of mathematics curriculum studies in Türkiye: trends and insights over two decades. SN Social Sciences, 6(10), Article 486. https://doi.org/10.1007/s43545-026-01783-0

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01783-0

Keywords: mathematics curriculum, Türkiye, systematic review, curriculum evaluation, education reform, constructivism, qualitative research, teacher perceptions, research methods, mathematics education, curriculum comparison, longitudinal studies

The review is notable for its methodological discipline. Where much of the existing literature takes a broad, sweeping approach to AI in schools, the Greek team narrowed its scope deliberately to the underexplored niche of lesson planning. The analysis follows the search–appraisal–synthesis–analysis framework, a structured procedure for identifying relevant studies, judging their quality, and extracting coherent findings from a heterogeneous body of work. The 53 studies were then organized around four central themes: the quality and pedagogical value of AI-generated plans, the challenges and limitations of the technology, teachers’ attitudes and perceptions, and proposed improvements and future directions. This thematic structure allows the authors to draw a clearer picture than previous, more diffuse surveys of the field.

The headline finding is a paradox that will resonate with any teacher who has experimented with ChatGPT, Google Gemini, or Microsoft Copilot. Large language models are genuinely good at helping educators organize content and save time. They can produce a complete, well-formatted lesson plan in seconds, complete with learning objectives, staged activities, and differentiation suggestions, a task that might otherwise consume an evening. Yet the literature consistently shows that this output often lacks the flexibility, contextual awareness, and pedagogical depth needed for actual classroom use. The plans look right on the page; whether they work with thirty restless adolescents on a Friday afternoon is another matter entirely.

The technical reason for this shortfall lies in how large language models work. These systems generate text by predicting likely continuations based on patterns in their training data, not by drawing on lived teaching experience or knowledge of a specific group of learners. The result, documented across the reviewed studies, is output that tends toward the generic. A model asked to plan a physics lesson for junior high school students cannot know that this particular class has already struggled with a prerequisite concept, or that the school lacks the equipment a hands-on activity requires. Studies cited in the review, including comparative analyses of ChatGPT and Gemini in physics education and content analyses of AI-generated mathematics plans, repeatedly identify this absence of situational judgment as the technology’s central weakness.

Contextual blindness extends to culture and history as well. Research on foreign language lesson plan creation has documented trends, variability, and historical biases in chatbot output, suggesting that the plans a model produces may quietly encode assumptions about curriculum, pedagogy, and even politics drawn from skewed training data. Work in Japanese teacher education has examined the social, cultural, and political dimensions of relying on generative AI in lesson planning, while studies of AI-generated English lesson plans for students with intellectual disabilities raise pointed questions about whether these tools can serve learners with specialized needs. A lesson plan is never a neutral document, and the review makes clear that outsourcing its drafting does not outsource its values.

Perhaps the most striking strand of evidence concerns what happens when humans and machines are compared directly. In one study of music education, teachers were asked to label lesson plans as AI-generated or human-made and to rate their quality, with results revealing how difficult that discrimination has become and how quality judgments vary. Other experimental work has asked whether lesson plans created by ChatGPT are more effective than teacher-designed ones, with mixed outcomes. Meanwhile, studies applying frameworks such as Universal Design for Learning to AI-generated plans have found the output serviceable but shallow, prompting one research team to title its analysis with the pointed question of whether AI-generated plans are better than nothing. The overall picture is of tools that clear a low bar convincingly but have not yet demonstrated superiority over experienced professionals.

Teachers’ own attitudes, the review’s third theme, are more nuanced than either hype or panic would suggest. Across studies of pre-service and in-service teachers in mathematics, science, English language teaching, social studies, and vocational education, educators consistently acknowledge the time savings and organizational help that chatbots provide. Many teacher education programs have begun integrating these tools directly, using ChatGPT as a reflection tool to promote the lesson planning competencies of trainee teachers, or as an assistant with which preservice secondary mathematics teachers rehearse their planning. Yet the same studies emphasize, almost without exception, the importance of teacher involvement in reviewing, adapting, and critically evaluating whatever the model produces. The consensus position is not replacement but supervision.

The review also documents a rapidly evolving effort to make the tools themselves better. Computer scientists have proposed systems such as LessonPlanner, designed to help novice teachers produce pedagogy-driven plans with large language models, and generation pipelines that use self-critique prompting, in which the model evaluates and revises its own draft plans. Retrieval augmented generation has been prototyped for Ugandan secondary schools facing a new national curriculum, grounding model output in authoritative local documents rather than relying on parametric memory alone. Fine-tuned assistants tailored specifically to lesson planning have been tested with teachers to compare perceptions and use. These engineering approaches attack the technology’s weaknesses directly, though the review suggests they remain early-stage.

Against these advances, the authors identify a significant shortfall in the existing literature: there is still limited empirical evidence directly comparing lesson plans designed by teachers with those produced by large language models in controlled settings. Much of the 53-study corpus relies on perceptions, small case studies, or qualitative analysis rather than head-to-head experimental comparisons measuring student outcomes. Until such evidence accumulates, claims that AI can plan lessons as well as or better than teachers rest on shaky ground. The review’s authors argue that as these tools become more common, the field needs practical research, thoughtful integration into teaching practice, and ongoing professional development to ensure responsible and effective use in education.

The broader lesson of the review is about the division of labor between human expertise and machine fluency. Large language models excel at producing well-structured text quickly, and lesson plans are, on their surface, exactly that. But effective teaching depends on knowing learners, adapting in real time, and exercising professional judgment, capacities that no current model possesses. The literature synthesized by the University of Thessaly team points toward a future in which AI handles the scaffolding of planning while teachers supply the pedagogical depth, contextual sensitivity, and critical oversight that turn a plausible document into a good lesson. That future is not automatic; it depends on the empirical research and teacher training the review calls for, and on educators who treat every machine-drafted plan as a first draft to be interrogated rather than a finished product to be delivered.

Subject of Research: The role of large language models in generating and evaluating lesson plans in education

Article Title: Evaluating the Role of Large Language Models in Lesson Planning: Insights from a Narrative Review

Article References: Failadis, V. A., Tasoulis, S. K., Georgakopoulos, S. V., & Plagianakos, V. P. (2026). Evaluating the Role of Large Language Models in Lesson Planning: Insights from a Narrative Review. Frontiers of Digital Education, 3(3), Article 25. https://doi.org/10.1007/s44366-026-0099-6

Image Credits: AI Generated

DOI: 10.1007/s44366-026-0099-6

Keywords: large language models, lesson planning, ChatGPT, generative AI, teacher perceptions, pedagogical quality, narrative review, teacher education, AI in education, instructional design, retrieval augmented generation, pre-service teachers

The team, led by Álvaro Barreras of the Universidad Internacional de La Rioja, surveyed 609 in-service teachers of mathematics, physics, chemistry, biology, geology, and technology across all of Spain’s autonomous communities and the autonomous city of Ceuta. The sample, drawn through convenience non-probability sampling, was large enough to meet accepted standards for populations exceeding 5,000 individuals. It skews toward public schools, which accounted for 80.8 percent of respondents, and toward urban settings, at 73.9 percent. Women made up 62.2 percent of participants, and nearly 37 percent had more than two decades of teaching experience. Data were collected in early 2022 using two previously validated instruments, one measuring teacher competences in the use of virtual simulations and the other measuring attitudes toward them.

The headline result is striking: only 54 percent of the teachers surveyed use virtual simulations habitually in their science classes. The rest either use them occasionally, at 29 percent, or never, at 17 percent. For a technology that the literature credits with improving student performance both on its own and in combination with real laboratories, that figure represents a substantial underuse. The study’s authors argue that this mismatch between proven benefit and classroom reality demands attention from both researchers and education policymakers, especially because simulations support scientific inquiry, mathematical competence, and conceptual model comprehension while simultaneously engaging students in ways traditional instruction often does not.

Statistical analysis revealed that age, gender, and school type had no significant effect on how frequently teachers used simulations. Instead, two variables mattered: years of teaching experience and the subject taught. Notably, the relationship with experience was not linear. Teachers with between 5 and 10 years in the classroom reported the highest frequency of use, followed by veterans with more than 20 years. The effect of experience was small by conventional benchmarks but classified as medium under Hattie’s educational interpretation. The authors suggest that younger teachers bring stronger general digital skills, while the most experienced teachers contribute superior pedagogical judgment about integrating technology, with the two mid-career and senior groups effectively combining those advantages.

Subject differences proved even more consequential. Physics and chemistry teachers and technology teachers emerged as the heaviest users, while biology and geology teachers and, most strikingly, mathematics teachers rarely reached for simulations. The effect size here was moderate by Cohen’s criteria and high by Hattie’s, with physics and chemistry and technology teachers showing the largest mean ranks. The mathematics finding particularly puzzled the researchers, given the wide availability of free simulation tools in that field and consistent evidence that such resources improve attitudes toward mathematics and mathematical competence. The authors conclude that targeted interventions are needed specifically for mathematics education, where underuse appears most acute despite obvious opportunities.

To understand what was holding teachers back, the study included an open-ended question, with responses analyzed qualitatively by four independent experts using an inductive-deductive framework. The difficulties clustered into four categories: lack of resources, teacher needs, student-related challenges, and curriculum design constraints. The most numerous category, accounting for more than 40 percent of reported difficulties, concerned the teachers themselves. Within it, three subcategories stood out: the poor fit between available simulations and teaching needs, with respondents complaining that tools were often too simple or too complex for their student profiles; the scarcity of formal training, forcing teachers to fund their own learning or teach themselves; and the limited usability of many simulators, which often ship without adequate tutorials.

Resource shortages came second. The dominant complaint was classroom logistics: not enough computers, unreliable devices, and slow internet connections. A smaller subset of teachers, less than 5 percent within that category, pointed to the digital divide at home, noting that some students lack devices and hesitate to use simulations outside school. Student-related difficulties rounded out the picture. About 40 percent of concerns in that category involved students’ limited fluency with simulation software, with one teacher observing that many teenagers use their phones only for social media and little else. Teachers also worried about trial-and-error behavior, in which students click randomly until they hit the right answer instead of reasoning first, along with distraction, low motivation for autonomous inquiry, and loss of focus on the activity’s actual learning goal.

Curriculum design issues, though the least numerous at roughly 10 percent of difficulties, painted a vivid picture of squeezed classroom time. Teachers described wasting precious minutes booting computers and explaining simulator interfaces, struggling to accommodate wide variation in student knowledge levels, and battling large class sizes and 55-minute sessions that leave little room for technological detours. Overly broad curricula compounded the problem. When the researchers tallied the individual subcategories across all responses, three issues together represented more than 60 percent of teachers’ concerns: classroom computer resources, the characteristics and availability of suitable simulations, and the need for training in how to find, select, and integrate them.

The training data underscored that concern. Only 19 percent of surveyed teachers had ever received formal training in virtual simulations, while 81 percent had not. Those most likely to have been trained were experienced teachers of mathematics and technology, an ironic twist given that mathematics teachers were among the least frequent users. Demand for training was nonetheless overwhelming: 50.1 percent rated general training as very necessary and another 27.6 percent as necessary. For training in searching for and selecting simulations, the figures rose to 52.1 percent and 28.6 percent, and for integration into the classroom, 46.1 percent and 28.4 percent. Notably, the need for training declined with experience in a roughly linear fashion, with the newest teachers, those with fewer than five years, expressing the greatest demand, and significant differences emerging between them and colleagues with more than 20 years.

The authors argue that the solution lies in coordinated educational policy and purpose-built training programs rather than in simply distributing more hardware. Effective training, they suggest, should connect teachers to curated repositories of quality simulators, build capacity to evaluate tools against specific learning objectives, demonstrate multiple didactic approaches including demonstration, home use, and guided inquiry projects, and prepare teachers to troubleshoot technical problems on the fly. Because the study was conducted in a single country with non-probabilistic sampling, the results cannot be generalized wholesale, and the authors call for future work comparing in-service and pre-service teachers and precisely defining what teachers in each scientific discipline need from simulation developers. Still, the message is clear: the barriers to virtual simulations are not about teacher skepticism or student ability alone, but about a systemic failure to equip educators with time, tools, and training, a failure that reformers ignore at the cost of a generation’s scientific literacy.

Subject of Research: Factors influencing secondary science teachers' use of virtual simulations in the classroom

Article Title: Factors influencing the use of virtual simulations by science teachers in secondary education

Article References: Barreras, Á., Moreno-Mediavilla, D., Gómez, R., & Palacios, A. (2026). Factors influencing the use of virtual simulations by science teachers in secondary education. Journal of New Approaches in Educational Research, 15(1), Article 1. https://doi.org/10.1007/s44322-025-00049-6

Image Credits: AI Generated

DOI: 10.1007/s44322-025-00049-6

Keywords: virtual simulations, science education, STEM teachers, secondary education, teacher training, educational technology, ICT integration, teacher perceptions, classroom resources, Spain, mathematics education, mixed methods